Strong associations of telomere length and mitochondrial copy number with suicidality and abuse history in adolescent depressed individuals.

Major depressive disorder (MDD) is highly prevalent in adolescents and is a major risk factor for suicidality. Recent evidence shows that accelerated cellular senescence/aging is associated with psychiatric illness, including depression, in adults. The present study examined if the relationships of telomere length (TL) and mitochondrial DNA copy number (mtDNAcn), two critical indicators of cellular senescence/aging, are altered in depressed adolescents and whether these alterations are associated with suicidality, early-life adversities, and other co-occuring factors. In genomic DNA isolated from 53 adolescents (ages 16-19, 19 MDD with suicide attempt/suicidal ideation [MDD + SI/SA], 14 MDD without SA/SI [MDD-SI/SA], and 20 healthy controls [HC]), TL and mtDNAcn were measured as the ratio between the number of telomere repeats and that of a single-copy nuclear-hemoglobin [HBG] gene or the amount of mtDNA (NADH dehydrogenase, subunit 1) relative to HBG. Our data show that TL was significantly lower, and mtDNAcn was significantly higher in the total MDD group than HC. TL was significantly lower and mtDNAcn was significantly higher in the MDD + SA/SI group than in the HC, whereas there were no differences in the MDD-SI/SA group. TL was positively correlated with mtDNAcn in both HC and MDD-SA/SI groups; however, TL was negatively correlated with mtDNAcn in MDD + SA/SI. Furthermore, TL was negatively correlated with the severity of both depression and anxiety, while mtDNAcn was positively correlated with the severity of prior emotional abuse. Our study indicates that cellular senescence is more advanced in depressed adolescents with suicidal ideation and that childhood emotional abuse may participate in such a process.

Examining the key determinants of the jordanian customer's adoption of genetically modified food.

Genetically modified food (GMF) is one of the most debated issues in the food market. There has been considerable interest from both academic researchers and policy makers regarding the antecedents and consequences of the commercial adoption of GMF applications. Conceptually, GMF can be defined as "Genetically modified (hereafter GM) foods are produced from genetically modified seeds or ingredients derived from plants or animals whose DNA has been manipulated using genetic engineering methods" [1, p. 2861]. However, only a limited number of studies have tested the related issues of GMF products from a customer perspective. Thus, this project intends to discover and examine the main drivers and hindrances in predicting customers' intention and buying decision behaviour in developing Arabian countries (i.e., Jordan). A diffusion of innovations (DOIs) model was selected as the theoretical basis for the current study project. A field survey study was conducted to collect the requested quantitative data from a convenience sample of Jordanian customers. Statistical results largely supported the role of relative advantage, compatibility, trialability, social approval, awareness, perceived risk and price value on the behavioural intention to adopt GMF products, which in turn significantly predicted actual adoption behaviour. The results of the current project will hopefully expand the current academic understanding of the main factors that predict Jordanian customers' perception and adoption of GMF products.

Responsible Digital Transformation for a Sustainable Society.

In the ever-evolving area of digital transformation, following responsible and sustainable practices is essential. This editorial article discusses the importance of responsible digital transformation, emphasizing the need for academia, private and public organizations, civil society, and individuals to work together in developing digital business models that generate shared value while addressing societal challenges. The article highlights the emergence of corporate digital responsibility (CDR) and the shift from industry 4.0 to industry 5.0, which focuses on human-centric approaches and human-AI partnerships. Furthermore, it underscores the need for interdisciplinary research and systematic approaches encompassing various dimensions of sustainability. By integrating sustainable ICT principles into digital transformation initiatives, organizations can contribute to a more sustainable and responsible digital future. The suggestions in this paper, coupled with the nice research contributions included in the special issue, seek to offer a broader foundation to support responsible digital transformations for sustainable societies.

Learnings from Industry 4.0 for transitioning towards Industry 4.0+: challenges and solutions for Indian pharmaceutical sector.

Industry 4.0 (I4.0) is helping production units to become smarter using cyber-physical systems and cognitive intelligence. The advanced diagnostics with I4.0 technologies (I4.0t) help in making the process highly flexible, resilient and autonomous. Still, the adoption of I4.0t especially in emerging economies like India is at a very slow pace. The present research has used an integrated approach i.e., Analytical Hierarchy Process-Combinative Distance-Based Assessment-Decision-Making Trial and Evaluation Laboratory to propose a barrier solution framework using data from pharmaceutical manufacturing sector. The findings reveal that "Costly venture" is found to be the most critical deterrent while "Customer awareness and satisfaction" is one of the potential solutions for I4.0t adoption. Further, lack of standardisation and fair benchmarking policies especially in the context of developing economies needs immediate attention. This article concludes by proposing a framework which will help to move from I4.0 towards Industry 4.0 + (I4.0+) which emphasises on role of collaboration between man and machine. And leads to sustainable supply chain management.

Exploring the Darkverse: A Multi-Perspective Analysis of the Negative Societal Impacts of the Metaverse.

The Metaverse has the potential to form the next pervasive computing archetype that can transform many aspects of work and life at a societal level. Despite the many forecasted benefits from the metaverse, its negative outcomes have remained relatively unexplored with the majority of views grounded on logical thoughts derived from prior data points linked with similar technologies, somewhat lacking academic and expert perspective. This study responds to the dark side perspectives through informed and multifaceted narratives provided by invited leading academics and experts from diverse disciplinary backgrounds. The metaverse dark side perspectives covered include: technological and consumer vulnerability, privacy, and diminished reality, human-computer interface, identity theft, invasive advertising, misinformation, propaganda, phishing, financial crimes, terrorist activities, abuse, pornography, social inclusion, mental health, sexual harassment and metaverse-triggered unintended consequences. The paper concludes with a synthesis of common themes, formulating propositions, and presenting implications for practice and policy.

Genomics in Treatment Development.

The Human Genome Project mapped the 3 billion base pairs in the human genome, which ushered in a new generation of genomically focused treatment development. While this has been very successful in other areas, neuroscience has been largely devoid of such developments. This is in large part because there are very few neurological or mental health conditions that are related to single-gene variants. While developments in pharmacogenomics have been somewhat successful, the use of genetic information in practice has to do with drug metabolism and adverse reactions. Studies of drug metabolism related to genetic variations are an important part of drug development. However, outside of cancer biology, the actual translation of genomic information into novel therapies has been limited. Epigenetics, which relates in part to the effects of the environment on DNA, is a promising newer area of relevance to CNS disorders. The environment can induce chemical modifications of DNA (e.g., cytosine methylation), which can be induced by the environment and may represent either shorter- or longer-term changes. Given the importance of environmental influences on CNS disorders, epigenetics may identify important treatment targets in the future.

Potential of Circulating miRNAs as Molecular Markers in Mood Disorders and Associated Suicidal Behavior.

Mood disorders are the most prevalent psychiatric disorders associated with significant disability, morbidity, and mortality. The risk of suicide is associated with severe or mixed depressive episodes in patients with mood disorders. However, the risk of suicide increases with the severity of depressive episodes and is often presented with higher incidences in bipolar disorder (BD) patients than in patients with major depression (MDD). Biomarker study in neuropsychiatric disorders is critical for developing better treatment plans by facilitating more accurate diagnosis. At the same time, biomarker discovery also provides more objectivity to develop state-of-the-art personalized medicine with increased accuracy through clinical interventions. Recently, colinear changes in miRNA expression between brain and systemic circulation have added great interest in examining their potential as molecular markers in mental disorders, including MDD, BD, and suicidality. A present understanding of circulating miRNAs in body fluids implicates their role in managing neuropsychiatric conditions. Most notably, their use as prognostic and diagnostic markers and their potential role in treatment response have significantly advanced our knowledge base. The present review discusses circulatory miRNAs and their underlying possibilities to be used as a screening tool for assessing major psychiatric conditions, including MDD, BD, and suicidal behavior.

An attitude-behavioral model to understand people's behavior towards tourism during COVID-19 pandemic.

The impact of pandemics on the tourism industry should be explored from the perspective of those who will travel, go to the tourist places on vacation, and avail services from tourism and hospitality-related organizations. This study has aimed to identify the reasons for the changed human psychology towards tourism during the COVID-19 Pandemic to develop an attitude-behavioral model. This investigation thus conducted an extensive empirical study among tourists to capture their social, emotional, and financial beliefs. The research then examined the measurement model through confirmatory factor analysis (CFA) before investigating the cause-effect relationship through the structural model. Analysis revealed that the negative effect of attitude on behavioral intention toward this new equilibrium is controlled by the emotional aspect of attitude. Furthermore this paper made several contributions to the literature on human psychology, crisis management, human behavior, marketing, and tourism.

An insight into the sprawling microverse of microRNAs in depression pathophysiology and treatment response.

Stress-related neuropathologies are pivotal in developing major depressive disorder (MDD) and are often governed by gene-regulatory changes. Being a stress-responsive gene-regulatory factor, microRNAs (miRNAs) have tremendous biomolecular potential to define an altered gene-regulatory landscape in the MDD brain. MiRNAs' regulatory roles in the MDD brain are closely aligned with changes in plasticity, neurogenesis, and stress-axis functions. MiRNAs act at the epigenetic interface between stress-induced environmental stimuli and cellular pathologies by triggering large-scale gene expression changes in a highly coordinated fashion. The parallel changes in peripheral circulation may provide an excellent opportunity for miRNA to devise more effective treatment strategies and help explore their potential as biomarkers in treatment response. This review discusses the role of miRNAs as epigenetic modifiers in the etiopathogenesis of MDD. Concurrently, key research is highlighted to show the progress in using miRNAs as predictive biomarkers for treatment response.

Dissecting early life stress-induced adolescent depression through epigenomic approach.

Early life stress (ELS), such as abuse and neglect during childhood, can lead to psychiatric disorders in later life. Previous studies have suggested that ELS can cause profound changes in gene expression through epigenetic mechanisms, which can lead to psychiatric disorders in adulthood; however, studies on epigenetic modifications associated with ELS and psychiatric disorders in adolescents are limited. Moreover, how these epigenetic modifications can lead to psychiatric disorders in adolescents is not fully understood. Commonly, DNA methylation, histone modification, and the regulation of noncoding RNAs have been attributed to the reprogramming of epigenetic profiling associated with ELS. Although only a few studies have attempted to examine epigenetic modifications in adolescents with ELS, existing evidence suggests that there are commonalities and differences in epigenetic profiling between adolescents and adults. In addition, epigenetic modifications are sex-dependent and are influenced by the type of ELS. In this review, we have critically evaluated the current evidence on epigenetic modifications in adolescents with ELS, particularly DNA methylation and the expression of microRNAs in both preclinical models and humans. We have also clarified the impact of ELS on psychiatric disorders in adolescents to predict the development of neuropsychiatric disorders and to prevent and recover these disorders through personalized medicine.

Is #SDG13 Trending Online? Insights from Climate Change Discussions on Twitter.

Anthropogenic activities over the past few decades have led to increased vulnerability of environmental and ecological stability on this planet. Accelerated climate change is one such subset of the environmental problems that threatens the very existence of humankind in twenty first century. Governments, United Nations (UN) and other humanitarian agencies across the globe have developed and devised strategies for climate action that requires grater public awareness and actions. Social media has played a vital role in information dissemination and raising public awareness of climate change in the digital era. To this aid, an upsurge has been documented in recent times regarding discussions over climate change with #SDG13 (Sustainable Development Goals) at its epicenter. Following the principles of Actor Network Theory (ANT) we analyzed a large volume of Twitter data to understand general citizens' perception and attitude towards climate change. Our findings unveil people's opinion on causes and concerns related to barriers of adopting a more sustainable consumption and lifestyle practice. There is also a growing apathy towards sluggish government actions that makes little difference. People were also found to exchange innovative concepts and measures towards mitigating the effects of climate change.

Fake news on Facebook and their impact on supply chain disruption during COVID-19.

Social media (SM) fake news has become a serious concern especially during COVID-19. In this study, we develop a research model to investigate to what extent SM fake news contributes to supply chain disruption (SCD), and what are the different SM affordances that contribute to SM fake news. To test the derived hypotheses with survey data, we have applied partial least square based structural equation modelling (PLS-SEM) technique. Further, to identify how different configurations of SC resilience (SCR) capabilities reduce SCD, we have used fuzzy set qualitative comparative analysis (fsQCA). The results show that SM affordances lead to fake news, which increases consumer panic buying (CPB); CPB in turn increases SCD. In addition, SM fake news directly increases SCD. The moderation test suggests that, SCR capability, as a higher-order construct, decreases the effect of CPB on SCD; however, neither of the capabilities individually moderates. Complimentarily, the fsQCA results suggest that no single capability but their three specific configurations reduce SCD. This work offers a new theoretical perspective to study SCD through SM fake news. Our research advances the knowledge of SCR from a configurational lens by adopting an equifinal means towards mitigating disruption. This research will also assist the operations and SC managers to strategize and understand which combination of resilience capabilities is the most effective in tackling disruptions during a crisis e.g., COVID-19. In addition, by identifying the relative role of different SM affordances, this study provides pragmatic insights into SM affordance measures that combat fake news on SM.

Has Covid-19 accelerated opportunities for digital entrepreneurship? An Indian perspective.

Covid-19 has challenged many businesses to orient themselves towards digital solutions for their survival. Due to the rising digital wave during Covid-19, there has been a plethora of opportunities for aspiring entrepreneurs to enter the market. Hence, this study focuses on understanding emerging areas and technologies for digital entrepreneurship. This study adopted a qualitative approach with semi-structured interviews through the lens of the diffusion of innovations theory. A total of 23 entrepreneurs responded and presented their views on Covid-19-induced opportunities for digital entrepreneurship. A structured process of open, axial, and selective coding was adopted for the thematic analysis. The study presents a framework based on four promising propositions. Results of the thematic analysis indicate the emergence of digital entrepreneurship opportunities in technology (EdTech, FinTech, cybersecurity), healthcare (diagnostics, virtual care, fitness), entertainment (over the top, gaming, social media), and e-commerce (contactless delivery, payment methods, augmented reality). In this study, entrepreneurs presented their views based on their experience with the platform or technology they operated. To this end, the present study offers implications both for scholars and entrepreneurs working in and aspiring to digital entrepreneurship along with future scope of research.

Managing buyer experience in a buyer-supplier relationship in MSMEs and SMEs.

Monitoring buyer experience provides competitive advantages for suppliers as buyers explore the market before reaching a salesperson. Still, not many B2B suppliers monitor their buyers' expectations throughout their procurement journey, especially in MSMEs and SMEs. In addition, the inductive research on evaluating buyer experience in buyer-supplier relationships is minimal, leaving an unexplored research area. This study explores antecedents of buyer experience during the buyer-supplier relationship in MSMEs and SMEs. Further, we investigate the nature of the influence of extracted precursors on the buyer experience. Firstly, we obtain the possible antecedents from the literature on buyer-supplier experience and supplier selection criteria. We also establish hypotheses based on transaction cost theory, resource-based view (RBV), and information processing view. Secondly, we employ an investigation based on the social media analytics-based approach to uncover the antecedents of buyer experience and their nature of influence on MSMEs and SME suppliers. We found that buyer experience is influenced by sustainable orientation, management capabilities (such as crisis management and process innovation), and suppliers' technology capabilities (digital readiness, big data analytical capability).

M6A RNA Methylation-Based Epitranscriptomic Modifications in Plasticity-Related Genes via miR-124-C/EBPα-FTO-Transcriptional Axis in the Hippocampus of Learned Helplessness Rats.

BACKGROUND: Impaired synaptic plasticity has been linked to dynamic gene regulatory network changes. Recently, gene regulation has been introduced with the emerging concept of unique N6-methyladenosine (m6A)-based reversible transcript methylation. In this study, we tested whether m6A RNA methylation may potentially serve as a link between the stressful insults and altered expression of plasticity-related genes. METHODS: Expression of plasticity genes Nr3c1, Creb1, Ntrk2; m6A-modifying enzymes Fto, methyltransferase like (Mettl)-3 and 14; DNA methylation enzymes Dnmt1, Dnmt3a; transcription factor C/ebp-α; and miRNA-124-3p were determined by quantitative polymerase chain reaction (qPCR) in the hippocampus of rats that showed susceptibility to develop stress-induced depression (learned helplessness). M6A methylation of plasticity-related genes was determined following m6A mRNA immunoprecipitation. Chromatin immunoprecipitation was used to examine the endogenous binding of C/EBP-α to the Fto promoter. MiR-124-mediated post-transcriptional inhibition of Fto via C/EBPα was determined using an in vitro model. RESULTS: Hippocampus of learned helplessness rats showed downregulation of Nr3c1, Creb1, and Ntrk2 along with enrichment in their m6A methylation. A downregulation in demethylating enzyme Fto and upregulation in methylating enzyme Mettl3 were also noted. The Fto promoter was hypomethylated due to the lower expression of Dnmt1 and Dnmt3a. At the same time, there was a lower occupancy of transcription factor C/EBPα on the Fto promoter. Conversely, C/ebp-α transcript was downregulated via induced miR-124-3p expression. CONCLUSIONS: Our study mechanistically linked defective C/EBP-α-FTO-axis, epigenetically influenced by induced expression of miR-124-3p, in modifying m6A enrichment in plasticity-related genes. This could potentially be linked with abnormal neuronal plasticity in depression.

Incorporating causality in energy consumption forecasting using deep neural networks.

Forecasting energy demand has been a critical process in various decision support systems regarding consumption planning, distribution strategies, and energy policies. Traditionally, forecasting energy consumption or demand methods included trend analyses, regression, and auto-regression. With advancements in machine learning methods, algorithms such as support vector machines, artificial neural networks, and random forests became prevalent. In recent times, with an unprecedented improvement in computing capabilities, deep learning algorithms are increasingly used to forecast energy consumption/demand. In this contribution, a relatively novel approach is employed to use long-term memory. Weather data was used to forecast the energy consumption from three datasets, with an additional piece of information in the deep learning architecture. This additional information carries the causal relationships between the weather indicators and energy consumption. This architecture with the causal information is termed as entangled long short term memory. The results show that the entangled long short term memory outperforms the state-of-the-art deep learning architecture (bidirectional long short term memory). The theoretical and practical implications of these results are discussed in terms of decision-making and energy management systems.

miR-218: A Stress-Responsive Epigenetic Modifier.

Understanding the epigenetic role of microRNAs (miRNAs) has been a critical development in the field of neuropsychiatry and in understanding their underlying pathophysiology. Abnormalities in miRNA expression are often seen as key to the pathogenesis of many stress-associated mental disorders, including major depressive disorder (MDD). Recent advances in omics biology have further contributed to this understanding and expanded the role of miRNAs in networking a diverse array of molecular pathways, which are essentially related to the stress adaptivity of a healthy brain. Studies have highlighted the role of many such miRNAs in causing maladaptive changes in the brain's stress axis. One such miRNA is miR-218, which is debated as a critical candidate for increased stress susceptibility. miR-218 is expressed throughout the brain, notably in the hippocampus and prefrontal cortex (PFC). It is expressed at various levels through life stages, as seen by adolescent and adult animal models. Until now, a minimal number of studies have been conducted on human subjects to understand its role in stress-related abnormalities in brain circuits. However, several studies, including animal and cell-culture models, have been used to understand the impact of miR-218 on stress response and hypothalamic-pituitary-adrenal (HPA) axis function. So far, expression changes in this miRNA have been found to regulate signaling pathways such as glucocorticoid signaling, serotonergic signaling, and glutamatergic signaling. Recently, the developmental role of miR-218 has generated interest, given its increasing expression from adolescence to adulthood and targeting the Netrin-1/DCC signaling pathway. Since miR-218 expression affects neuronal development and plasticity, it is expected that a change in miR-218 expression levels over the course of development may negatively impact the process and make individuals stress-susceptible in adulthood. In this review, we describe the role of miR-218 in stress-induced neuropsychiatric conditions with an emphasis on stress-related disorders.

The effect of IV ketamine in patients with major depressive disorder and elevated features of borderline personality disorder.

BACKGROUND: Comorbid borderline personality disorder and major depressive disorder is common and often not adequately responsive to standard antidepressant therapies. Ketamine is a potentially life-saving option. METHODS: 153 adult patients with MDD were assessed with the Personality Assessment Inventory (PAI) Borderline Subscale. Data was normally distributed with a mean + SD of 38.95 + 11.54. Patients >1 SD above the mean were assigned to the MDD + BF group. All others were assigned to the MDD-BF group. Patients were administered IV ketamine 0.5 mg/kg of ketamine over 40 min. Mood was assessed using the Beck Depression Inventory-II at baseline, 3 and 24 h post-ketamine. Scores between the MDD + BF and MDD-BF group at each time point were compared using t-test or analysis of covariance (ANCOVA) model. The primary outcome was response at 24 h. RESULTS: The LS mean change in BDI at 24 h was -23.8 (15.3) for MDD + BF and -21.0 (13.5) for MDD-BF (F [1151] = 0.043, p = 0.51). The LS mean change in BDI at 3 h was -21.3 (13.2) for MDD + BF and -19.6 (13.2) for MDD-BF (F[1151] = 0.045, p = 0.83). The LS mean change in BDI at 14 days was -23.2 (15.3) for MDD + BF and -15.3 (15.2) for MDD-BF (F[1130] = 4.24, p = 0.04). LIMITATIONS: People in the MDD + BF group were not necessarily diagnosable with borderline personality disorder. CONCLUSIONS: These data indicate that IV ketamine is effective in MDD patients with and without elevated borderline features. This can provide clinicians some reassurance about using ketamine in this population.